Adaptive Boundary Research Articles

Perturbation Sensitivity Analysis and Dynamic Topology Optimization for Heat Conduction Structure

Topology optimization is a fundamental problem for steady heat conduction. Due to the unidirectional treatment for the intermediate density elements in the traditional topology optimization, we propose a Bi-Directional Interpolation Model (BDIM) that intermediate density elements are judged by a threshold, and establish optimization model. Besides, considering the generation of new hole boundary in the process of heat conduction enhancement topology optimization, we study the perturbation sensitivity analysis with respect to new hole, and present an adaptive dynamic boundary method for the new boundary in the optimization process. Furthermore, based on the domain perturbation technique and Lebesgue differential theory, the topological derivative formulas with different objective functions subjected to three kinds of boundary conditions are derived for the control system of Poisson equation. Finally, a number of numerical examples are presented to demonstrate the feasibility and effectiveness of the proposed method for designing the heat conduction structure.

Robust adaptive boundary control of semilinear PDE systems using a dyadic controller

SummaryIn this paper, we describe a dyadic adaptive control framework for output tracking in a class of semilinear systems of partial differential equations with boundary actuation and unknown distributed nonlinearities. The dyadic adaptive control framework uses the linear terms in the system to split the plant into 2 virtual subsystems, one of which contains the nonlinearities, whereas the other contains the control input. Full‐plant‐state feedback is used to estimate the unmeasured individual states of the 2 subsystems as well as the nonlinearities. The control signal is designed to ensure that the controlled subsystem tracks a suitably modified reference signal. We prove the well posedness of the closed‐loop system rigorously and derive conditions for closed‐loop stability and robustness using finite‐gain stability theory.

Adaptive Control of a Flexible String System With Input Hysteresis

In this brief, a vibration suppression scheme is investigated for a flexible string system with input hysteresis. The input hysteresis is formulated as a linear desired input and a “disturbance-like” term, whose unknown bound is then estimated by an adaptive law. Without constructing a hysteresis inverse, adaptive boundary control is designed to suppress the vibrations of the flexible string, cope with the uncertainties of system parameters, and tackle the hysteresis nonlinearities. Based on the extended LaSalle’s invariance principle, asymptotic stability of the closed-loop system is also manifested. Simulations are also provided to show the effectiveness of the designed control.

An On-Demand Same-Day Delivery Service Using Direct Peer-to-Peer Transshipment Strategies

As the same-day delivery service becomes increasingly popular among e-commerce customers, it demands fast, cheap, and flexible on-demand delivery service. This paper proposes, formulates, and evaluates a new on-demand, same-day delivery (ODSD) strategy using direct peer-to-peer transshipment (P2PT). P2PT involves package relays among multiple couriers to extend beyond the normal service range of a single courier; this is done directly via effective collaboration and coordination among couriers. Three P2PT variants are investigated in this paper: P2PT-1 with one single inter-zonal ODSD service request (pickup and delivery in two different service zones), P2PT-M with multiple inter-zonal ODSD requests, and P2PT-RT with real-time inter-zonal demand. An adaptive boundary relaxation (ABR) heuristic algorithm is proposed and evaluated for its solution performance. The P2PT delivery paradigm is also compared with the most responsive and naive ODSD strategy of direct shipping. It is found that while P2PT tends to incur longer travel time than direct shipping, it provides the ODSD service without having to expand and maintain a larger fleet of vehicles (and thus drivers) or incurring extra labor cost. As the economy of scale of ODSD demand increases, those advantages of P2PT will only become more prominent. Our investigations have also found that the efficiency of P2PT, measured by the additional travel time incurred per ODSD service request, improves initially with the economy of scale, and then seems to flatten out in the static demand scenario or worsen in the real-time demand scenario as the number of service requests increases.

Fast Specimen Boundary Tracking and Local Imaging with Scanning Probe Microscopy.

An efficient and adaptive boundary tracking method is developed to confine area of interest for high-efficiency local scanning. By using a boundary point determination criterion, the scanning tip is steered with a sinusoidal waveform while estimating azimuth angle and radius ratio of each boundary point to accurately track the boundary of targets. A local scan region and path are subsequently planned based on the prior knowledge of boundary tracking to reduce the scan time. Boundary tracking and local scanning methods have great potential not only for fast dimension measurement but also for sample surface topography and physical characterization, with only scanning region of interest. The performance of the proposed methods was verified by using the alternate current mode scanning ion-conductance microscopy, tapping, and PeakForce modulation atomic force microscopy. Experimental results of single/multitarget boundary tracking and local scanning of target structures with complex boundaries demonstrate the flexibility and validity of the proposed method.

Synchronization of Nonlinear Complex Spatio-Temporal Networks Using Adaptive Boundary Control and Pinning Adaptive Boundary Control

There are many behaviors with spatio-temporal characteristics in nature. Complex spatio-temporal networks (CSNs)-based on partial differential equations are to process such issues. This paper studies two synchronization boundary control methods. An adaptive boundary controller is first studied to ensure synchronization of the CSNs. Furthermore, a pinning adaptive boundary controller is proposed to achieve synchronization of the CSNs. Two sufficient criteria of synchronization and pinning synchronization are respectively obtained. Finally, two numerical examples demonstrate the effectiveness of the proposed theoretical results.

Power Optimization in Self-Organizing MEC Based Heterogeneous Small Cell Networks

Mobile edge computing (MEC) technology migrates the cloud computing platform to the edge of the mobile access network, which reduces the end-to-end delay of mobile service delivery and improves the user experience. However, since the number of the deployed small cell base stations (BSs) is larger than the macro BSs, automatic deployment can be used to control deployment costs. In this paper, we study the adaptive boundary algorithm of indoor small cell BSs and propose a power optimization scheme in self-organizing MEC-based heterogeneous small cell networks. According to the actual environment, the indoor small cell BS can be deployed quickly and flexibly. And the coverage of the small cell BS can be optimized by automatically adjusting the power parameters. Considering the coverage and spectral efficiency of the macro BS and the small cell BS, the performance indicators of the optimization program and results evaluation is proposed. Finally, the simulation results show that the proposed algorithm and scheme can control the deployment cost and improve the optimization coverage of macro BSs and small cell BSs under the control cost.

A Unified Design Approach to Repetitive Learning Control for Systems Subject to Fractional Uncertainties

Fractional uncertainties are involved in many practical systems. Currently, there is a lack of research results about such general class of nonlinear systems in the context of learning control. This paper presents a Lyapunov-synthesis approach to repetitive learning control (RLC) being unified due to the use of the direct parametrization and adaptive bounding techniques. To effectively handle fractional uncertainties, the estimation method for such uncertainties is elaborated to facilitate the controller design and convergence analysis. Its novelty lies in the less requirement for the knowledge about the system undertaken. Unsaturated- and saturated-learning algorithms are, respectively, characterized by which both the boundedness of the variables in the closed-loop system undertaken and the asymptotical convergence of the tracking error are established. Experimental results are provided to verify the effectiveness of the presented learning control.

Robust output feedback stabilization for a flexible marine riser system

The aim of this paper is to develop a boundary control for the vibration reduction of a flexible marine riser system in the presence of parametric uncertainties and system states obtained inaccurately. To this end, an adaptive output feedback boundary control is proposed to suppress the riser’s vibration fusing with observer-based backstepping, high-gain observers and robust adaptive control theory. In addition, the parameter adaptive laws are designed to compensate for the system parametric uncertainties, and the disturbance observer is introduced to mitigate the effects of external environmental disturbance. The uniformly bounded stability of the closed-loop system is achieved through rigorous Lyapunov analysis without any discretisation or simplification of the dynamics in the time and space, and the state observer error is ensured to exponentially converge to zero as time grows to infinity. In the end, the simulation and comparison studies are carried out to illustrate the performance of the proposed control under the proper choice of the design parameters.

Computational simulation of postoperative pulmonary flow distribution in Alagille patients with peripheral pulmonary artery stenosis.

Up to 90% of individuals with Alagille syndrome have congenital heart diseases. Peripheral pulmonary artery stenosis (PPS), resulting in right ventricular hypertension and pulmonary flow disparity, is one of the most common abnormalities, yet the hemodynamic effects are ill-defined, and optimal patient management and treatment strategies are not well established. The purpose of this pilot study is to use recently refined computational simulation in the setting of multiple surgical strategies, to examine the influence of pulmonary artery reconstruction on hemodynamics in this population. Based on computed tomography angiography and cardiac catheterization data, preoperative pulmonary artery models were constructed for 4 patients with Alagille syndrome with PPS (all male, age range: 0.6-2.9 years), and flow simulations with deformable walls were performed. Surgeon directed virtual surgery, mimicking the surgical procedure, was then performed to derive postoperative models. Postoperative simulation-derived hemodynamics and blood flow distribution were then compared with the clinical results. Simulations confirmed substantial resistance, resulting from preoperative severe ostial stenoses, and the use of newly developed adaptive outflow boundary conditions led to excellent agreement with in vivo measurements. Relief of PPS decreased pulmonary artery pressures and improved pulmonary flow distribution both in vivo and in silico with good correlation. Using adaptive outflow boundary conditions, computational simulations can estimate postoperative overall pulmonary flow distribution in patients with Alagille syndrome after pulmonary artery reconstruction. Obstruction relief along with pulmonary artery vasodilation determines postoperative pulmonary flow distribution and newer methods can incorporate these physiologic changes. Evolving blood flow simulations may be useful in surgical or transcatheter planning and in understanding the complex interplay among various obstructions in patients with peripheral pulmonary stenosis.

Automatic Balloon Snake Method for Topology Adaptive Water Boundary Extraction: Using GF-1 Satellite Imagery as an Example

Topology adaptive boundary extraction for water in satellite images using parametric snakes remains challenging in the domain of image segmentation due to the inability of topology inflexible parametric snakes (TIPS) to split and merge curves and the limited accuracy or inefficiency of topology flexible parametric snakes (TFPS). Based on the balloon snake (B-snake) method, an outstanding representative of TIPS, this paper proposed the automatic B-snake (AB-snake) method capable of automatic initialization and topology transformation to overcome the drawbacks of nonautomatic initialization and topology inflexibility of the B-snake method while ensuring both high accuracy and efficiency of TFPS. Six GF-1 wide field view satellite images covering different inner island numbers, water body sizes, boundary complexities, boundary clarities, and background complexities were used as experimental images. To test its feasibility and advantages, the extracted results of the AB-snake method were compared with those of the B-snake and the orthogonal topology adaptive snake (OT-snake) methods, a newer representative of TFPS. The results demonstrated that the AB-snake method could effectively implement automatic initialization and topology transformation, successfully meeting its design objectives. Four indices, including correctness, completeness, area overlap measure, and efficiency, were adopted to quantitatively assess the performances of the B-snake, the AB-snake, and the OT-snake methods. The results suggested that the proposed AB-snake method not only significantly outperformed the B-snake method in topology collision handling but also demonstrated great advantages over the OT-snake method in accuracy. The applicability, sensitivity, parameter selection, and limitations of the AB-snake method were also elaborated.

WANG TILE SIZE IN TERMS OF CIRCULAR PARTICLE DYNAMICS

The main advantage of the Wang tiling concept for material engineering is ability to create large material domains with a relatively small set of tiles. Such idea allows both a reduction of computational demands and preserving heterogeneity of a reconstructed media in comparison with traditional cell concepts. This work is dealing with a random heterogeneous material composed of monodisperse circular hard particles within a matrix. The Wang tile sets are generated via algorithm with molecular dynamics and adaptive boundaries approach. Even though previous works proved usefulness of the Wang tiling for material reconstruction, still plenty of questions remain unanswered. In here we would like to provide simulations with emphasis on the overall particle distribution and the ratio of hard disc number to tile size. The results and discussion should followers help with settings of both tile generations and the tiling algorithms when creating samples of various degree of heterogeneity.

Robust adaptive constrained boundary control for a suspension cable system of a helicopter

SummaryIn this article, the problems of modeling and controlling are investigated for a suspension cable system of a helicopter with input saturation, system parameter uncertainties, and external disturbances by using the boundary control method. In accordance with the Hamilton's principle, the model of the suspension cable system of a helicopter is established by using a set of partial differential and ordinary differential equations. Considering nonsymmetric saturation constraint, the auxiliary systems are designed to handle with the effect of input saturation. Considering Lyapunov's direct method and the designed auxiliary systems, two robust adaptive boundary controllers are provided by the actuators at the helicopter and the box. Under the proposed controllers, the error between the bottom payload and the target location and the vibration range are uniformly ultimately bounded. Moreover, they will converge to a small neighborhood of zero by selecting the suitable parameters. Meanwhile, to guarantee the validity of the proposed adaptive boundary control laws, some sufficient conditions are raised. Simulation results are provided to verify that the effectiveness of the designed controllers in this paper.

Mechanisms Underlying N-back Training: Response Consistency During Training Influences Training Outcome

In the last decade, working memory (WM) training has become one of the most intensively studied approaches in cognitive training research. Nevertheless, the systematic study of the transfer mechanisms that influence WM training outcome is still a relatively new approach despite its potential to stabilize training outcome. In this study, we introduce the beneficial effect of lower reaction time variability (RTV) during cognitive training on the effectiveness of the training. The aim of the present study was to investigate this mechanism by comparing the effects of traditional visual n-back training to those of an adapted consistency n-back training designed to reduce RTV. The consistency n-back training included direct reaction time feedback and an adaptive reaction time boundary system to elicit constant reaction time and thus increased attentional control during training. Seventy-seven participants (mean age 22.6 years) were randomly assigned to the two training groups and compared to a passive control group. In line with our theoretical assumptions, the enriched training demands of the consistency n-back task converted into higher near transfer on test versions of both training tasks and higher transfer on a structurally different and more complex WM task. More detailed results indicated that the traditional n-back training task promotes task-structure-dependent strategy acquisition (preventing far transfer), whereas the consistency n-back training promotes a less task-specific increase in WM efficiency. We discuss these two transfer mechanisms and conclude that low RTV during training increases transfer by enhancing the involvement of attentional control processes during training.

Adaptive Wavelet BEM for Boundary Integral Equations: Theory and Numerical Experiments

ABSTRACTWe are concerned with the numerical treatment of boundary integral equations by the adaptive wavelet boundary element method. In particular, we consider the second kind Fredholm integral equation for the double layer potential operator on patchwise smooth manifolds contained in ℝ3. The corresponding operator equations are treated by adaptive implementations that are in complete accordance with the underlying theory. The numerical experiments demonstrate that adaptive methods really pay off in this setting. The observed convergence rates fit together very well with the theoretical predictions based on the Besov regularity of the exact solution.

Boundary Control of 2-D Burgers' PDE: An Adaptive Dynamic Programming Approach.

In this paper, an adaptive dynamic programming-based near optimal boundary controller is developed for partial differential equations (PDEs) modeled by the uncertain Burgers' equation under Neumann boundary condition in 2-D. Initially, Hamilton-Jacobi-Bellman equation is derived in infinite-dimensional space. Subsequently, a novel neural network (NN) identifier is introduced to approximate the nonlinear dynamics in the 2-D PDE. The optimal control input is derived by online estimation of the value function through an additional NN-based forward-in-time estimation and approximated dynamic model. Novel update laws are developed for estimation of the identifier and value function online. The designed control policy can be applied using a finite number of actuators at the boundaries. Local ultimate boundedness of the closed-loop system is studied in detail using Lyapunov theory. Simulation results confirm the optimizing performance of the proposed controller on an unstable 2-D Burgers' equation.

Aspects of an adaptive finite element method for the fractional Laplacian: A priori and a posteriori error estimates, efficient implementation and multigrid solver

We develop all of the components needed to construct an adaptive finite element code that can be used to approximate fractional partial differential equations, on non-trivial domains in d≥1 dimensions. Our main approach consists of taking tools that have been shown to be effective for adaptive boundary element methods and, where necessary, modifying them so that they can be applied to the fractional PDE case. Improved a priori error estimates are derived for the case of quasi-uniform meshes which are seen to deliver sub-optimal rates of convergence owing to the presence of singularities. Attention is then turned to the development of an a posteriori error estimate and error indicators which are suitable for driving an adaptive refinement procedure. We assume that the resulting refined meshes are locally quasi-uniform and develop efficient methods for the assembly of the resulting linear algebraic systems and their solution using iterative methods, including the multigrid method. The storage of the dense matrices along with efficient techniques for computing the dense matrix–vector products needed for the iterative solution is also considered. The performance and efficiency of the resulting algorithm is illustrated for a variety of examples.

Interplay of phase sequence and electronic structure in the modulated martensites of Mn2NiGa from first-principles calculations

We investigate relative stability, structural properties and electronic structure of various modulated martensites of the magnetic shape memory alloy Mn$_{2}$NiGa by means of density functional theory. We observe that the instability in the high-temperature cubic structure first drives the system to a structure where modulation shuffles with a period of six atomic planes are taken into account. The driving mechanism for this instability is found to be the nesting of the minority band Fermi surface, in a similar way as established for the prototype system Ni$_{2}$MnGa. In agreement with experiments, we find 14M modulated structures with orthorhombic and monoclinic symmetries having energies lower than other modulated phases with same symmetry. In addition, we also find energetically favourable 10M modulated structures which have not been observed experimentally for this system yet. The relative stability of various martensites is explained in terms of changes in the electronic structures near the Fermi level, affected mostly by the hybridisation of Ni and Mn states. Our results indicate that the maximum achievable magnetic field-induced strain in Mn$_{2}$NiGa would be larger than in Ni$_{2}$MnGa. However, the energy costs for creating nanoscale adaptive twin boundaries are found to be one order of magnitude higher than that in Ni$_{2}$MnGa.

Robust adaptive vibration control for an uncertain flexible Timoshenko robotic manipulator with input and output constraints

ABSTRACTThe problems of the constraints and the vibration suppression are investigated for the flexible Timoshenko robotic manipulator in this paper. Robust adaptive boundary control laws with the disturbance observes are designed to guarantee the convergence of the feedback flexible Timoshenko robotic manipulator system with the uncertain parameters and the states are proven to be uniform bounded. In addition, the proposed boundary controls are verified to be effectiveness by the numeral experiments.

Robust adaptive fuzzy control for a class of nonlinear coupled ODE–beam systems with boundary uncertainty

This paper investigates a robust adaptive fuzzy control problem for a class of nonlinear ordinary differential equations (ODEs) coupled with a beam equation subject to boundary uncertainty. A fuzzy control scheme based on the Takagi–Sugeno (T–S) fuzzy model is employed for the nonlinear ODE subsystem with ODE state feedback. For the beam with boundary uncertainty, a robust adaptive fuzzy boundary control scheme is adopted, where a linear controller via boundary measurements is used to stabilize the beam, and a robust adaptive fuzzy compensator is utilized to counteract the boundary uncertainty. The asymptotic stabilization condition is derived for the nonlinear coupled ODE–beam system by means of the Lyapunov's direct method, which is provided in terms of a set of bilinear matrix inequalities (BMIs). Furthermore, a two-step procedure is presented to solve the BMI feasibility problem by the existing linear matrix inequality (LMI) optimization techniques. Finally, a simulation study is conducted on a flexible spacecraft to demonstrate the effectiveness of the proposed method.